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» Reinforcement Learning Estimation of Distribution Algorithm
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ATAL
2008
Springer
15 years 1 months ago
Efficient multi-agent reinforcement learning through automated supervision
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
EC
2010
176views ECommerce» more  EC 2010»
14 years 9 months ago
Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation
Estimation of distribution algorithms (EDAs) that use marginal product model factorizations have been widely applied to a broad range of, mainly binary, optimization problems. In ...
Roberto Santana, Pedro Larrañaga, Jos&eacut...
ICML
2005
IEEE
16 years 15 days ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
GLOBECOM
2010
IEEE
14 years 9 months ago
Reinforcement Learning for Link Adaptation in MIMO-OFDM Wireless Systems
Machine learning algorithms have recently attracted much interest for effective link adaptation due to their flexibility and ability to capture more environmental effects implicitl...
Sungho Yun, Constantine Caramanis
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
14 years 10 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup